Current Issue : July - September Volume : 2018 Issue Number : 3 Articles : 5 Articles
We explore how to leverage the performance of face feature points detection on mobile terminals from3 aspects. First, we optimize\nthe models used in SDM algorithms via PCA and Spectrum Clustering. Second, we propose an evaluation criterion using Linear\nDiscriminative Analysis to choose the best local feature descriptions which plays a critical role in feature points detection. Third, we\ntake advantage ofmulticore architecture of mobile terminal and parallelize the optimized SDMalgorithm to improve the efficiency\nfurther.The experiment observations show that our final accomplished GPC-SDM (improved Supervised Descent Method using\nspectrum clustering, PCA, andGPU acceleration) suppresses the memory usage, which is beneficial and efficient to meet the realtime\nrequirements....
In wireless sensor networks (WSNs), many applications require a high reliability for the sensing data forwarding to sink. Due to\nthe lossy nature of wireless channels, achieving reliable communication through multihop forwarding can be very challenging.\nBroadcast technology is an effective way to improve the communication reliability so that the data can be received by multiple\nreceiver nodes.As long as the data of any one of the receiver nodes is transmitted to the sink, the data can be transmitted successfully.\nIn this paper, a cross-layer optimization protocol named Adaptive transmission Power control based Reliable data Forwarding\n(APRF) scheme by using broadcast technology is proposed to improve the reliability of network and reduce communication delay.\nThemain contributions of this paper are as follows: (1) for general data aggregation sensor networks, through the theoretical analysis,\nthe energy consumption characteristics of the network are obtained. (2) According to the case that the energy consumption of nearsink\narea is high and that in far-sink area is low, a cross-layer optimization method is adopted,which can effectively improve the data\ncommunication by increasing the transmission power of the remaining energy nodes. (3) Since the reliability of communication is\nimproved by increasing the transmission power of the node, the number of retransmissions of the data packet is reduced, so that the\ndelay of the packet reaching the sink node is reduced. The theoretical and experimental results show that, applying APRF scheme\nunder initial transmission power of 0 dBm, although the lifetime dropped by 13.77%, delay could be reduced by 40.37%, network\nreliability could be reduced by 10.08%, and volume of data arriving at sink increased by 10.08% compared with retransmission-only\nmechanism....
Reliable detection of cognitive load would benefit the design of intelligent assistive navigation aids for the visually impaired\n(VIP). Ten participants with various degrees of sight loss navigated in unfamiliar indoor and outdoor environments, while their\nelectroencephalogram (EEG) and electrodermal activity (EDA) signals were being recorded. In this study, the cognitive load of\nthe tasks was assessed in real time based on a modification of the well-established event-related (de)synchronization (ERD/ERS)\nindex.We present an in-depth analysis of the environments that mostly challenge people fromcertain categories of sight loss and we\npresent an automatic classification of the perceived difficulty in each time instance, inferred fromtheir biosignals. Given the limited\nsize of our sample, our findings suggest that there are significant differences across the environments for the various categories of\nsight loss.Moreover, we exploit cross-modal relations predicting the cognitive load in real time inferring on features extracted from\nthe EDA. Such possibility paves the way for the design on less invasive, wearable assistive devices that take into consideration the\nwell-being of the VIP....
Mobile edge computing (MEC) enables battery-powered mobile nodes to acquire information technology services at the network\nedge. These nodes desire to enjoy their service under power saving. The sampling rate invariant detection (SRID) is the first\ndownclockingWiFi technique that can achieve this objective.With SRID, a node detects one packet arrival at a downclocked rate.\nUpon a successful detection, the node reverts to a full-clocked rate to receive the packet immediately. To ensure that a node acquires\nits service immediately, the detection performance (namely, the miss-detection probability and the false-alarmprobability) of SRID\nis of importance. This paper is the first one to theoretically study the crucial impact of SRID attributes (e.g., tolerance threshold,\ncorrelation threshold, and energy ratio threshold) on the packet detection performance. ExtensiveMonte Carlo experiments show\nthat our theoretical model is very accurate. This study can help system developers set reasonable system parameters for WiFi\ndownclocking....
Vehicular safety applications have much significance in preventing road accidents and fatalities. Among others, cellular networks\nhave been under investigation for the procurement of these applications subject to stringent requirements for latency, transmission\nparameters, and successful delivery of messages. Earlier contributions have studied utilization of Long-TermEvolution (LTE) under\nsingle cell, Friis radio, or simplified higher layer. In this paper, we study the utilization of LTE undermulticell andmultipath fading\nenvironment and introduce the use of adaptive awareness range. Then, we propose an algorithm that uses the concept of quality\nof service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of\nbackground traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill\nvehicular application requirements through extensive system-level simulations.The results show that, by using an awareness range\nof up to 250m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles\nin an area of 2 Ã?â?? 2 km2.The urban vehicular radio environment has a significant impact and decreases the probability for end-toend\ndelay to be ââ?°Â¤100ms from 93%ââ?¬â??97% to 76%ââ?¬â??78% compared to the Friis radio environment. The proposed algorithm reduces\nthe amount of vehicular application traffic from 21Mbps to 13Mbps, while improving the probability of end-to-end delay being\nââ?°Â¤100ms by 20%. Lastly, use ofMAClayer control elements brings the processing ofmessages towards the edge of network increasing\ncapacity of the system by about 50%....
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